Ilit Raz, Founder and CEO of Joonko – Interview Series

Ilit Raz is the founder and CEO of Joonko, a platform that helps businesses apply AI to their diversity sourcing strategy. Today her company works with Adidas, American Express, Crocs and PayPal. She’s raised over $38.5M and the company has grown 500% for two consecutive years.

What initially attracted you to computer science?

Technology is one of the largest and most successful industries in Israel, so I’ve always been exposed to the industry in one way or another throughout my life. When I entered the army, I earned the opportunity to work in a technology unit where I managed the development of security software and spent time learning about computer science. From there I was hooked and knew I wanted to pursue it as a career once I left the army.

When did you initially become exposed to various gaps in the industry such as salary and promotional gaps?

During my first couple of years working at private software companies, I wasn’t personally aware of the bias women faced. Then, I started to network with technologists that happened to be women. I quickly became aware of how big the problem was after listening to the stories these women shared about being talked over, ignored, or not getting credit for their ideas.

Can you share the genesis story behind Joonko?

I have a degree in computer science and a background in software engineering and NLP. I have personally experienced both unconscious, and conscious, bias through my professional surroundings, and a group of female product managers I was a part of also exposed me to workplace issues that were more than just salary gaps. This looks like meetings getting scheduled when women or parents need to leave work or witnessing who gets to talk or present during meetings. Although these instances seem minor, they are significant and influential when you’re the person being impacted.

I came to understand this was a more widespread problem, so I decided to use my technical background––I have a degree in CS and a background in software engineering and NLP––and tackle it head-on by creating a new technology solution, which is how Joonko was born.

How does Joonko source the talent pool of applicants from diverse and underrepresented backgrounds?

Our proprietary algorithm first uses natural language processing and computer vision to scan public data on the candidates that are referred to us. We look for data that validates whether someone self identifies as underrepresented. For example, if a person has “she/her” pronouns on their LinkedIn, we can infer that they might self identify as a woman and assign that data point a point. If the person’s profile collects enough points, we invite them to our talent network, and once they sign up, they further validate our assumption by telling us how they identify.

How does Joonko then vet this talent?

We use a combination of human touch and technology to match candidates with the open positions that are a fit. First, each candidate that joins our network is referred by the hiring team they recently interviewed with, but couldn’t hire them. The hiring teams only refer candidates that made it to the final round thus ensuring they are high quality candidates. From there, we use natural language processing to match the candidate with the company and role that is the right fit. We collect keywords from their resume and the role they originally interviewed for, then compare that with the jobs marketed on our platform. Most models only use two data sets, so using three instead increases our ability to make the right match.

How does Joonko assist companies with retaining this talent?

We assist companies in retaining talent throughout the recruiting process by integrating with the applicant tracking system. Our integration allows us to pull data, in aggregate, about how far Joonko candidates get through the pipeline. Wherever we see a drop off in comparison to non-Joonko candidates, we work with companies to either improve the matching or improve their recruitment process.

What are some other ways that Joonko uses AI in its hiring or match making process?

We leverage computer vision and natural language processing to determine whether a candidate self-identifies as underrepresented. We use natural language processing to match candidates with the roles in our pool and we use machine learning to improve the matching process as candidates select the roles they’re interested in. Lastly, the matching and referral is automated from end to end. Recruiters don’t have to do anything until they decide to interview a candidate referred by Joonko.

Could you discuss the benefits of a diversified hiring pool to avoid AI bias?

The way we look at it is, the more underrepresented candidates you can attract and interview, the more data you can audit for human and technological bias. Bias, at its core, occurs when a model (or person) is used to seeing similar data over and over again. When you heavily invest in candidate diversity you can train your technology, and the recruiting team that uses it, to contribute to the diversity flywheel.

What are some other reasons diversity should be a priority for companies?

Lots of companies typically rely on referrals to fill open roles, which data shows can lead to a homogeneous workforce. I believe it’s important for companies to put a spotlight on overlooked talent – including ‘silver medalist candidates’ who made it to the final stages at top companies but didn’t end up getting the job.

Not only is prioritizing DE&I objectively the fair and right thing to do and an important part of a forward-thinking, equitable society, but it’s also simply good for business – companies that prioritize these efforts are more productive and successful, while employees are happier and stick around longer.

Do you have any final advice for women who are looking at leaping in computer science or AI?

Find communities of women you can lean on when things get tough. The future of the artificial intelligence industry depends on the participation of women, but is currently dominated by men. The faster you can build a network of women who share your experiences, the more likely you are to be supported and thrive in the industry.

Thank you for the great interview, readers who wish to learn more should visit Joonko.